Datasets:
image
imagewidth (px) 320
320
| wrist
imagewidth (px) 320
320
| conversations
dict | annotation
stringclasses 0
values |
|---|---|---|---|
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[119, 17], [148, 35], [167, 69], [166, 92], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ë±ĭ, ìľ¾, Ôij, à¬ī, ðĸ¥, íĵ¶, ðŁİij], [áĪ¨, ìĦIJ, ḻ, ãĪª, âĶ½, ðĿĻ¸, ðŁİij], [ìĿ¿, ðŁķŀ, áĴĮ, âļĤ, âĨ·, âĿ«, ðŁİij], [Ѩ, ðŁĸ¶, áĭ©, á¶ı, â½Ĺ, âºŁ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[120, 17], [158, 41], [167, 74], [166, 97], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[áĪ¨, ìĦIJ, ḻ, ãĪª, âĶ½, ðĿĻ¸, ðŁİij], [ìĿ¿, ðŁķŀ, áĴĮ, âļĤ, âĨ·, âĿ«, ðŁİij], [Ѩ, ðŁĸ¶, áĭ©, á¶ı, â½Ĺ, âºŁ, ðŁİij], [ðŁĶĢ, á¼®, à²Ł, âĻĻ, â½Ĺ, â½Ĺ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[124, 20], [158, 41], [167, 74], [166, 97], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ìĿ¿, ðŁķŀ, áĴĮ, âļĤ, âĨ·, âĿ«, ðŁİij], [Ѩ, ðŁĸ¶, áĭ©, á¶ı, â½Ĺ, âºŁ, ðŁİij], [ðŁĶĢ, á¼®, à²Ł, âĻĻ, â½Ĺ, â½Ĺ, ðŁİij], [ðŁĶĥ, ðŁĹģ, 맳, ìı±, â½Ĺ, â½Ĺ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[130, 25], [164, 48], [167, 80], [166, 97], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[Ѩ, ðŁĸ¶, áĭ©, á¶ı, â½Ĺ, âºŁ, ðŁİij], [ðŁĶĢ, á¼®, à²Ł, âĻĻ, â½Ĺ, â½Ĺ, ðŁİij], [ðŁĶĥ, ðŁĹģ, 맳, ìı±, â½Ĺ, â½Ĺ, ðŁİij], [ê¸ij, ðŁĸij, áĪĬ, ðŁķĭ, â°Ł, â½Ĺ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_8><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_8><DEPTH_56><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[138, 31], [166, 56], [167, 80], [166, 97], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðŁĶĢ, á¼®, à²Ł, âĻĻ, â½Ĺ, â½Ĺ, ðŁİij], [ðŁĶĥ, ðŁĹģ, 맳, ìı±, â½Ĺ, â½Ĺ, ðŁİij], [ê¸ij, ðŁĸij, áĪĬ, ðŁķĭ, â°Ł, â½Ĺ, ðŁİij], [á¿IJ, ðŁĶ¤, áīIJ, á©ĭ, ðŁħĵ, âŀ¶, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[148, 35], [167, 63], [167, 84], [166, 102], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðŁĶĥ, ðŁĹģ, 맳, ìı±, â½Ĺ, â½Ĺ, ðŁİij], [ê¸ij, ðŁĸij, áĪĬ, ðŁķĭ, â°Ł, â½Ĺ, ðŁİij], [á¿IJ, ðŁĶ¤, áīIJ, á©ĭ, ðŁħĵ, âŀ¶, ðŁİij], [íĵŃ, ðŁĶ¤, Êĵ, áīIJ, ðĿĻ¸, ãĦĵ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_101><DEPTH_75><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[158, 41], [167, 63], [167, 84], [166, 102], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ê¸ij, ðŁĸij, áĪĬ, ðŁķĭ, â°Ł, â½Ĺ, ðŁİij], [á¿IJ, ðŁĶ¤, áīIJ, á©ĭ, ðŁħĵ, âŀ¶, ðŁİij], [íĵŃ, ðŁĶ¤, Êĵ, áīIJ, ðĿĻ¸, ãĦĵ, ðŁİij], [íĽľ, á¡Į, áīIJ, íķ®, ðĿĺı, ÆĪ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_56><DEPTH_75><DEPTH_75><DEPTH_8><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[164, 48], [167, 69], [167, 88], [166, 102], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[á¿IJ, ðŁĶ¤, áīIJ, á©ĭ, ðŁħĵ, âŀ¶, ðŁİij], [íĵŃ, ðŁĶ¤, Êĵ, áīIJ, ðĿĻ¸, ãĦĵ, ðŁİij], [íĽľ, á¡Į, áīIJ, íķ®, ðĿĺı, ÆĪ, ðŁİij], [ï¤ħ, ë¯ij, áĪ¨, áĪĬ, ðĿĻº, ðĿķ±, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 56], [167, 74], [167, 88], [166, 102], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[íĵŃ, ðŁĶ¤, Êĵ, áīIJ, ðĿĻ¸, ãĦĵ, ðŁİij], [íĽľ, á¡Į, áīIJ, íķ®, ðĿĺı, ÆĪ, ðŁİij], [ï¤ħ, ë¯ij, áĪ¨, áĪĬ, ðĿĻº, ðĿķ±, ðŁİij], [ï¤Ĩ, ë¯ij, ìĦIJ, Êĵ, ðĿĵ¾, ðĿķ¡, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 63], [167, 80], [166, 92], [166, 106], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[íĽľ, á¡Į, áīIJ, íķ®, ðĿĺı, ÆĪ, ðŁİij], [ï¤ħ, ë¯ij, áĪ¨, áĪĬ, ðĿĻº, ðĿķ±, ðŁİij], [ï¤Ĩ, ë¯ij, ìĦIJ, Êĵ, ðĿĵ¾, ðĿķ¡, ðŁİij], [ï¦ĥ, ìĭ², ìĦIJ, Éĺ, íĵ¬, ðĸ¥¨, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 69], [167, 80], [166, 92], [166, 106], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤ħ, ë¯ij, áĪ¨, áĪĬ, ðĿĻº, ðĿķ±, ðŁİij], [ï¤Ĩ, ë¯ij, ìĦIJ, Êĵ, ðĿĵ¾, ðĿķ¡, ðŁİij], [ï¦ĥ, ìĭ², ìĦIJ, Éĺ, íĵ¬, ðĸ¥¨, ðŁİij], [ï¦ĥ, à½ħ, íķ®, áĪ¨, ðĿĵķ, íĭį, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 74], [167, 84], [166, 97], [166, 106], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤Ĩ, ë¯ij, ìĦIJ, Êĵ, ðĿĵ¾, ðĿķ¡, ðŁİij], [ï¦ĥ, ìĭ², ìĦIJ, Éĺ, íĵ¬, ðĸ¥¨, ðŁİij], [ï¦ĥ, à½ħ, íķ®, áĪ¨, ðĿĵķ, íĭį, ðŁİij], [ï¦ĥ, ï®ı, ìı±, áĪĬ, ðĿĺIJ, ḻ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 80], [167, 88], [166, 97], [166, 106], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¦ĥ, ìĭ², ìĦIJ, Éĺ, íĵ¬, ðĸ¥¨, ðŁİij], [ï¦ĥ, à½ħ, íķ®, áĪ¨, ðĿĵķ, íĭį, ðŁİij], [ï¦ĥ, ï®ı, ìı±, áĪĬ, ðĿĺIJ, ḻ, ðŁİij], [ï¤Ĩ, ê¸ij, Ḱ, ï®ı, 롼, áłĦ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_8><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 84], [166, 92], [166, 102], [164, 110], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¦ĥ, à½ħ, íķ®, áĪ¨, ðĿĵķ, íĭį, ðŁİij], [ï¦ĥ, ï®ı, ìı±, áĪĬ, ðĿĺIJ, ḻ, ðŁİij], [ï¤Ĩ, ê¸ij, Ḱ, ï®ı, 롼, áłĦ, ðŁİij], [ï¤ħ, ë¯ij, âĦ¬, áĮĥ, áłĦ, á¨ģ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 88], [166, 92], [166, 102], [164, 110], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¦ĥ, ï®ı, ìı±, áĪĬ, ðĿĺIJ, ḻ, ðŁİij], [ï¤Ĩ, ê¸ij, Ḱ, ï®ı, 롼, áłĦ, ðŁİij], [ï¤ħ, ë¯ij, âĦ¬, áĮĥ, áłĦ, á¨ģ, ðŁİij], [ï¦ĥ, ìĿ©, Úİ, á¼®, à°³, áī¨, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 92], [166, 97], [166, 106], [164, 110], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤Ĩ, ê¸ij, Ḱ, ï®ı, 롼, áłĦ, ðŁİij], [ï¤ħ, ë¯ij, âĦ¬, áĮĥ, áłĦ, á¨ģ, ðŁİij], [ï¦ĥ, ìĿ©, Úİ, á¼®, à°³, áī¨, ðŁİij], [ï¤Ĩ, ìŤ, á½Ŀ, ï®ı, Ý¥, áIJ§, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_26><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 97], [166, 102], [166, 106], [164, 110], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤ħ, ë¯ij, âĦ¬, áĮĥ, áłĦ, á¨ģ, ðŁİij], [ï¦ĥ, ìĿ©, Úİ, á¼®, à°³, áī¨, ðŁİij], [ï¤Ĩ, ìŤ, á½Ŀ, ï®ı, Ý¥, áIJ§, ðŁİij], [ï¤Ĩ, áĮ½, ðŁĨĴ, âļĤ, Ý¥, áĮĶ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_26><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 102], [166, 106], [164, 110], [164, 113], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¦ĥ, ìĿ©, Úİ, á¼®, à°³, áī¨, ðŁİij], [ï¤Ĩ, ìŤ, á½Ŀ, ï®ı, Ý¥, áIJ§, ðŁİij], [ï¤Ĩ, áĮ½, ðŁĨĴ, âļĤ, Ý¥, áĮĶ, ðŁİij], [里, íĽľ, ë±ĭ, ìľ¾, Ý¥, à²Ł, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_69><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 106], [164, 110], [164, 113], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤Ĩ, ìŤ, á½Ŀ, ï®ı, Ý¥, áIJ§, ðŁİij], [ï¤Ĩ, áĮ½, ðŁĨĴ, âļĤ, Ý¥, áĮĶ, ðŁİij], [里, íĽľ, ë±ĭ, ìľ¾, Ý¥, à²Ł, ðŁİij], [ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_26><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[164, 110], [164, 113], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤Ĩ, áĮ½, ðŁĨĴ, âļĤ, Ý¥, áĮĶ, ðŁİij], [里, íĽľ, ë±ĭ, ìľ¾, Ý¥, à²Ł, ðŁİij], [ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, Ý¥], [里, Ýĵ, áĶħ, ॱ, Ȳ, à¬ī, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[164, 113], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[里, íĽľ, ë±ĭ, ìľ¾, Ý¥, à²Ł, ðŁİij], [ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, Ý¥], [里, Ýĵ, áĶħ, ॱ, Ȳ, à¬ī, Ý¥], [ðIJŃĵ, âĽı, ⽺, â°ł, ÔĪ, à°³, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, Ý¥], [里, Ýĵ, áĶħ, ॱ, Ȳ, à¬ī, Ý¥], [ðIJŃĵ, âĽı, ⽺, â°ł, ÔĪ, à°³, Ý¥], [ðĿĻľ, ï¨Ĭ, â½Ĺ, â½Ĺ, ʶ, à¤ij, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 113], [166, 86], [138, 62], [84, 58], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[里, Ýĵ, áĶħ, ॱ, Ȳ, à¬ī, Ý¥], [ðIJŃĵ, âĽı, ⽺, â°ł, ÔĪ, à°³, Ý¥], [ðĿĻľ, ï¨Ĭ, â½Ĺ, â½Ĺ, ʶ, à¤ij, Ý¥], [áĴĮ, âĨ¤, â°Ł, â°¡, ì»ģ, ì»ģ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 112], [162, 79], [126, 58], [75, 59], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðIJŃĵ, âĽı, ⽺, â°ł, ÔĪ, à°³, Ý¥], [ðĿĻľ, ï¨Ĭ, â½Ĺ, â½Ĺ, ʶ, à¤ij, Ý¥], [áĴĮ, âĨ¤, â°Ł, â°¡, ì»ģ, ì»ģ, Ý¥], [íĭį, ðĿļı, âķĬ, àłĮ, ᳬ, áĶŃ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_69><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 105], [162, 79], [126, 58], [75, 59], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðĿĻľ, ï¨Ĭ, â½Ĺ, â½Ĺ, ʶ, à¤ij, Ý¥], [áĴĮ, âĨ¤, â°Ł, â°¡, ì»ģ, ì»ģ, Ý¥], [íĭį, ðĿļı, âķĬ, àłĮ, ᳬ, áĶŃ, Ý¥], [ðĿĺļ, ðĿĵ¾, áļĮ, ðĿĶĵ, ìł°, ìĿ¿, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_26><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_26><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[168, 95], [156, 72], [112, 58], [75, 59], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[áĴĮ, âĨ¤, â°Ł, â°¡, ì»ģ, ì»ģ, Ý¥], [íĭį, ðĿļı, âķĬ, àłĮ, ᳬ, áĶŃ, Ý¥], [ðĿĺļ, ðĿĵ¾, áļĮ, ðĿĶĵ, ìł°, ìĿ¿, Ý¥], [áĻ³, íĭį, âĿ«, áĬĴ, ìī¡, á¼®, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_75><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 86], [147, 67], [112, 58], [75, 59], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[íĭį, ðĿļı, âķĬ, àłĮ, ᳬ, áĶŃ, Ý¥], [ðĿĺļ, ðĿĵ¾, áļĮ, ðĿĶĵ, ìł°, ìĿ¿, Ý¥], [áĻ³, íĭį, âĿ«, áĬĴ, ìī¡, á¼®, Ý¥], [âĶ½, âļ£, âĿ«, Úİ, ìŤ, ðŁĶ¤, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_26><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[162, 79], [138, 62], [97, 58], [67, 58], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðĿĺļ, ðĿĵ¾, áļĮ, ðĿĶĵ, ìł°, ìĿ¿, Ý¥], [áĻ³, íĭį, âĿ«, áĬĴ, ìī¡, á¼®, Ý¥], [âĶ½, âļ£, âĿ«, Úİ, ìŤ, ðŁĶ¤, Ý¥], [ãī«, ḻ, ðĿĻ¸, ìī¡, ê¸ij, ðŁĶ¢, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_32><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_56><DEPTH_26><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[156, 72], [138, 62], [97, 58], [67, 58], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[áĻ³, íĭį, âĿ«, áĬĴ, ìī¡, á¼®, Ý¥], [âĶ½, âļ£, âĿ«, Úİ, ìŤ, ðŁĶ¤, Ý¥], [ãī«, ḻ, ðĿĻ¸, ìī¡, ê¸ij, ðŁĶ¢, Ý¥], [âĴ¡, ðĿĵ°, âĻĻ, âļ§, ðŁķŀ, ðŁĶĢ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_75><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_9><DEPTH_75><DEPTH_26><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[147, 67], [126, 58], [84, 58], [67, 58], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[âĶ½, âļ£, âĿ«, Úİ, ìŤ, ðŁĶ¤, Ý¥], [ãī«, ḻ, ðĿĻ¸, ìī¡, ê¸ij, ðŁĶ¢, Ý¥], [âĴ¡, ðĿĵ°, âĻĻ, âļ§, ðŁķŀ, ðŁĶĢ, Ý¥], [â¼Ń, ðĿĻľ, ì¥ī, ë»ħ, ðŁı¯, ðŁĶĢ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_69><DEPTH_101><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_125><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_26><DEPTH_26><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[138, 62], [112, 58], [84, 58], [67, 58], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ãī«, ḻ, ðĿĻ¸, ìī¡, ê¸ij, ðŁĶ¢, Ý¥], [âĴ¡, ðĿĵ°, âĻĻ, âļ§, ðŁķŀ, ðŁĶĢ, Ý¥], [â¼Ń, ðĿĻľ, ì¥ī, ë»ħ, ðŁı¯, ðŁĶĢ, Ý¥], [â°ij, Ýĵ, ìĦIJ, ðŁħ±, ðŁİij, ðŁķĿ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_69><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_56><DEPTH_30><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_75><DEPTH_26><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_8><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[126, 58], [97, 58], [75, 59], [64, 59], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[âĴ¡, ðĿĵ°, âĻĻ, âļ§, ðŁķŀ, ðŁĶĢ, Ý¥], [â¼Ń, ðĿĻľ, ì¥ī, ë»ħ, ðŁı¯, ðŁĶĢ, Ý¥], [â°ij, Ýĵ, ìĦIJ, ðŁħ±, ðŁİij, ðŁķĿ, Ý¥], [ãī«, à¤ij, ëĶī, ìł°, ðŁĶĩ, êĻĭ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_69><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_32><DEPTH_75><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[112, 58], [97, 58], [75, 59], [64, 59], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[â¼Ń, ðĿĻľ, ì¥ī, ë»ħ, ðŁı¯, ðŁĶĢ, Ý¥], [â°ij, Ýĵ, ìĦIJ, ðŁħ±, ðŁİij, ðŁķĿ, Ý¥], [ãī«, à¤ij, ëĶī, ìł°, ðŁĶĩ, êĻĭ, Ý¥], [ðĿĺIJ, Ý¥, ìł°, á¶ı, ⼤, áĪĬ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_75><DEPTH_101><DEPTH_75><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[97, 58], [84, 58], [67, 58], [64, 59], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[â°ij, Ýĵ, ìĦIJ, ðŁħ±, ðŁİij, ðŁķĿ, Ý¥], [ãī«, à¤ij, ëĶī, ìł°, ðŁĶĩ, êĻĭ, Ý¥], [ðĿĺIJ, Ý¥, ìł°, á¶ı, ⼤, áĪĬ, Ý¥], [âĶŀ, ðĿĵ°, áĪ¨, á¶ı, ᨸ, ì»ģ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_26><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_26><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_26><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_69><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[84, 58], [75, 59], [67, 58], [64, 59], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ãī«, à¤ij, ëĶī, ìł°, ðŁĶĩ, êĻĭ, Ý¥], [ðĿĺIJ, Ý¥, ìł°, á¶ı, ⼤, áĪĬ, Ý¥], [âĶŀ, ðĿĵ°, áĪ¨, á¶ı, ᨸ, ì»ģ, Ý¥], [ðĿĵŀ, á¿ļ, áĪĬ, íĬŃ, ðĿĵŀ, à°µ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_8><DEPTH_26><DEPTH_101><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_75><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[75, 59], [67, 58], [64, 59], [64, 61], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðĿĺIJ, Ý¥, ìł°, á¶ı, ⼤, áĪĬ, Ý¥], [âĶŀ, ðĿĵ°, áĪ¨, á¶ı, ᨸ, ì»ģ, Ý¥], [ðĿĵŀ, á¿ļ, áĪĬ, íĬŃ, ðĿĵŀ, à°µ, Ý¥], [里, ìĽ¢, á¶ı, à´´, ʶ, à²Ł, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_26><DEPTH_101><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_101><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[67, 58], [64, 59], [64, 61], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[âĶŀ, ðĿĵ°, áĪ¨, á¶ı, ᨸ, ì»ģ, Ý¥], [ðĿĵŀ, á¿ļ, áĪĬ, íĬŃ, ðĿĵŀ, à°µ, Ý¥], [里, ìĽ¢, á¶ı, à´´, ʶ, à²Ł, Ý¥], [ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_26><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[64, 59], [64, 61], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðĿĵŀ, á¿ļ, áĪĬ, íĬŃ, ðĿĵŀ, à°µ, Ý¥], [里, ìĽ¢, á¶ı, à´´, ʶ, à²Ł, Ý¥], [ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, ðŁİij], [ìľ¾, à¤ij, ï¥ł, áĶĬ, ÔĪ, ʶ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_26><DEPTH_101><DEPTH_30><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_101><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[64, 61], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[里, ìĽ¢, á¶ı, à´´, ʶ, à²Ł, Ý¥], [ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, ðŁİij], [ìľ¾, à¤ij, ï¥ł, áĶĬ, ÔĪ, ʶ, ðŁİij], [ìŤ, ðĿļģ, íĵ¶, áĭ©, 맳, à°µ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_26><DEPTH_101><DEPTH_30><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_101><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, ðŁİij], [ìľ¾, à¤ij, ï¥ł, áĶĬ, ÔĪ, ʶ, ðŁİij], [ìŤ, ðĿļģ, íĵ¶, áĭ©, 맳, à°µ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[119, 17], [150, 36], [167, 70], [166, 93], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[⤦, â¡¢, à²Ł, áĶĬ, ðĿķį, ïŃ², ðŁİij], [à½ħ, ê¸ij, á¨ģ, áĴĮ, âĽı, ðĿĻ½, ðŁİij], [ìĭ², ðŁķŀ, áIJ§, á©ĭ, âĶ², ê¦Ķ, ðŁİij], [ðŁĸĩ, ðŁĹģ, áĮĦ, á¿ļ, â½Ĺ, â½Ĺ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[121, 17], [159, 43], [167, 75], [166, 98], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[à½ħ, ê¸ij, á¨ģ, áĴĮ, âĽı, ðĿĻ½, ðŁİij], [ìĭ², ðŁķŀ, áIJ§, á©ĭ, âĶ², ê¦Ķ, ðŁİij], [ðŁĸĩ, ðŁĹģ, áĮĦ, á¿ļ, â½Ĺ, â½Ĺ, ðŁİij], [ðŁĵª, áºĢ, à¤ij, á©ĭ, â½Ĺ, â½Ĺ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[126, 21], [159, 43], [167, 75], [166, 98], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ìĭ², ðŁķŀ, áIJ§, á©ĭ, âĶ², ê¦Ķ, ðŁİij], [ðŁĸĩ, ðŁĹģ, áĮĦ, á¿ļ, â½Ĺ, â½Ĺ, ðŁİij], [ðŁĵª, áºĢ, à¤ij, á©ĭ, â½Ĺ, â½Ĺ, ðŁİij], [ðŁĶ¢, Ѩ, â¡¢, ìı±, â½Ĺ, â½Ĺ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[131, 26], [164, 50], [167, 81], [166, 98], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðŁĸĩ, ðŁĹģ, áĮĦ, á¿ļ, â½Ĺ, â½Ĺ, ðŁİij], [ðŁĵª, áºĢ, à¤ij, á©ĭ, â½Ĺ, â½Ĺ, ðŁİij], [ðŁĶ¢, Ѩ, â¡¢, ìı±, â½Ĺ, â½Ĺ, ðŁİij], [ìī¡, ðŁķ¢, áĨº, à´´, 嘆, â½Ĺ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_8><DEPTH_75><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_56><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[139, 31], [167, 57], [167, 81], [166, 98], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðŁĵª, áºĢ, à¤ij, á©ĭ, â½Ĺ, â½Ĺ, ðŁİij], [ðŁĶ¢, Ѩ, â¡¢, ìı±, â½Ĺ, â½Ĺ, ðŁİij], [ìī¡, ðŁķ¢, áĨº, à´´, 嘆, â½Ĺ, ðŁİij], [â¡¢, ðŁĶ¤, áĮĥ, á¾Ķ, ðĿļı, âĩŀ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[150, 36], [167, 64], [167, 85], [166, 103], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðŁĶ¢, Ѩ, â¡¢, ìı±, â½Ĺ, â½Ĺ, ðŁİij], [ìī¡, ðŁķ¢, áĨº, à´´, 嘆, â½Ĺ, ðŁİij], [â¡¢, ðŁĶ¤, áĮĥ, á¾Ķ, ðĿļı, âĩŀ, ðŁİij], [íķ±, ðŁĶ©, ï®ı, Õĥ, ðĿĻ°, âĿ«, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_69><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_8><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[159, 43], [167, 64], [167, 85], [166, 103], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ìī¡, ðŁķ¢, áĨº, à´´, 嘆, â½Ĺ, ðŁİij], [â¡¢, ðŁĶ¤, áĮĥ, á¾Ķ, ðĿļı, âĩŀ, ðŁİij], [íķ±, ðŁĶ©, ï®ı, Õĥ, ðĿĻ°, âĿ«, ðŁİij], [ï¤ħ, âĦ¬, áĮ½, ðŁħ±, ðĿĺı, ðĿļı, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_56><DEPTH_75><DEPTH_75><DEPTH_8><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[164, 50], [167, 70], [167, 88], [166, 103], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[â¡¢, ðŁĶ¤, áĮĥ, á¾Ķ, ðĿļı, âĩŀ, ðŁİij], [íķ±, ðŁĶ©, ï®ı, Õĥ, ðĿĻ°, âĿ«, ðŁİij], [ï¤ħ, âĦ¬, áĮ½, ðŁħ±, ðĿĺı, ðĿļı, ðŁİij], [ï¤ħ, ë¯ij, áĪĬ, áīIJ, ðĿĻº, ðĿķ¡, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 57], [167, 75], [167, 88], [166, 103], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[íķ±, ðŁĶ©, ï®ı, Õĥ, ðĿĻ°, âĿ«, ðŁİij], [ï¤ħ, âĦ¬, áĮ½, ðŁħ±, ðĿĺı, ðĿļı, ðŁİij], [ï¤ħ, ë¯ij, áĪĬ, áīIJ, ðĿĻº, ðĿķ¡, ðŁİij], [ï¤Ĩ, ë¯ij, ë¯ij, ðŁĨĴ, ðĿij³, ðĿķį, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_75><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 64], [167, 81], [166, 93], [166, 107], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤ħ, âĦ¬, áĮ½, ðŁħ±, ðĿĺı, ðĿļı, ðŁİij], [ï¤ħ, ë¯ij, áĪĬ, áīIJ, ðĿĻº, ðĿķ¡, ðŁİij], [ï¤Ĩ, ë¯ij, ë¯ij, ðŁĨĴ, ðĿij³, ðĿķį, ðŁİij], [ï¦ĥ, ìĿ©, ìĭ², Õĥ, íĵ¬, ðĸ¥, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_69><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 70], [167, 81], [166, 93], [166, 107], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤ħ, ë¯ij, áĪĬ, áīIJ, ðĿĻº, ðĿķ¡, ðŁİij], [ï¤Ĩ, ë¯ij, ë¯ij, ðŁĨĴ, ðĿij³, ðĿķį, ðŁİij], [ï¦ĥ, ìĿ©, ìĭ², Õĥ, íĵ¬, ðĸ¥, ðŁİij], [ï¦ĥ, áĨº, ï®ı, áĪ¾, ðĿķ±, 롼, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_69><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 75], [167, 85], [166, 98], [166, 107], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤Ĩ, ë¯ij, ë¯ij, ðŁĨĴ, ðĿij³, ðĿķį, ðŁİij], [ï¦ĥ, ìĿ©, ìĭ², Õĥ, íĵ¬, ðĸ¥, ðŁİij], [ï¦ĥ, áĨº, ï®ı, áĪ¾, ðĿķ±, 롼, ðŁİij], [ï¦ĥ, ì¥ī, ë¼Ŀ, Õĥ, ðĿĶĵ, á¨ģ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 81], [167, 88], [166, 98], [166, 107], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¦ĥ, ìĿ©, ìĭ², Õĥ, íĵ¬, ðĸ¥, ðŁİij], [ï¦ĥ, áĨº, ï®ı, áĪ¾, ðĿķ±, 롼, ðŁİij], [ï¦ĥ, ì¥ī, ë¼Ŀ, Õĥ, ðĿĶĵ, á¨ģ, ðŁİij], [ï¤Ĩ, 㳬, á¡Į, ðŁķĭ, ê²Ļ, á¨ģ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_30><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 85], [166, 93], [166, 103], [164, 111], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¦ĥ, áĨº, ï®ı, áĪ¾, ðĿķ±, 롼, ðŁİij], [ï¦ĥ, ì¥ī, ë¼Ŀ, Õĥ, ðĿĶĵ, á¨ģ, ðŁİij], [ï¤Ĩ, 㳬, á¡Į, ðŁķĭ, ê²Ļ, á¨ģ, ðŁİij], [ï¤ħ, ë¼Ŀ, âĦ¬, áĪĬ, áĴĮ, áłĦ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_75><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 88], [166, 93], [166, 103], [164, 111], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¦ĥ, ì¥ī, ë¼Ŀ, Õĥ, ðĿĶĵ, á¨ģ, ðŁİij], [ï¤Ĩ, 㳬, á¡Į, ðŁķĭ, ê²Ļ, á¨ģ, ðŁİij], [ï¤ħ, ë¼Ŀ, âĦ¬, áĪĬ, áĴĮ, áłĦ, ðŁİij], [ï¦ĥ, ìŤ, ðŁĹģ, Ḱ, à¬ī, áģ¼, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_8><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 93], [166, 98], [166, 107], [164, 111], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤Ĩ, 㳬, á¡Į, ðŁķĭ, ê²Ļ, á¨ģ, ðŁİij], [ï¤ħ, ë¼Ŀ, âĦ¬, áĪĬ, áĴĮ, áłĦ, ðŁİij], [ï¦ĥ, ìŤ, ðŁĹģ, Ḱ, à¬ī, áģ¼, ðŁİij], [ï¤Ĩ, ìĿ¿, 㳬, áĨº, Ýĵ, áĶħ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_26><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_26><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 98], [166, 103], [166, 107], [164, 111], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤ħ, ë¼Ŀ, âĦ¬, áĪĬ, áĴĮ, áłĦ, ðŁİij], [ï¦ĥ, ìŤ, ðŁĹģ, Ḱ, à¬ī, áģ¼, ðŁİij], [ï¤Ĩ, ìĿ¿, 㳬, áĨº, Ýĵ, áĶħ, ðŁİij], [ï¦ĥ, á¶ı, à´´, âĻĻ, Ý¥, áĭ©, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_26><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 103], [166, 107], [164, 111], [164, 113], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¦ĥ, ìŤ, ðŁĹģ, Ḱ, à¬ī, áģ¼, ðŁİij], [ï¤Ĩ, ìĿ¿, 㳬, áĨº, Ýĵ, áĶħ, ðŁİij], [ï¦ĥ, á¶ı, à´´, âĻĻ, Ý¥, áĭ©, ðŁİij], [里, ï¦ĥ, ì³ħ, ì»ģ, Ý¥, à°µ, ðŁİij]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_69><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_69><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_28><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 107], [164, 111], [164, 113], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¤Ĩ, ìĿ¿, 㳬, áĨº, Ýĵ, áĶħ, ðŁİij], [ï¦ĥ, á¶ı, à´´, âĻĻ, Ý¥, áĭ©, ðŁİij], [里, ï¦ĥ, ì³ħ, ì»ģ, Ý¥, à°µ, ðŁİij], [ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_26><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[164, 111], [164, 113], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¦ĥ, á¶ı, à´´, âĻĻ, Ý¥, áĭ©, ðŁİij], [里, ï¦ĥ, ì³ħ, ì»ģ, Ý¥, à°µ, ðŁİij], [ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, Ý¥], [里, áĢı, ê³Ĥ, áĴĮ, ðŁıĩ, à¬ī, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[164, 113], [164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[里, ï¦ĥ, ì³ħ, ì»ģ, Ý¥, à°µ, ðŁİij], [ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, Ý¥], [里, áĢı, ê³Ĥ, áĴĮ, ðŁıĩ, à¬ī, Ý¥], [ðIJŃĵ, á¥Ķ, â½Ĺ, â½Ĺ, Ôij, à°³, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 2. The subtask goals are: pick up the biscuit box at [164, 113] and place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[164, 113]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ï¨Ĥ, ðIJŃĵ, ì»ģ, â¡¢, ÔĪ, à¤ij, Ý¥], [里, áĢı, ê³Ĥ, áĴĮ, ðŁıĩ, à¬ī, Ý¥], [ðIJŃĵ, á¥Ķ, â½Ĺ, â½Ĺ, Ôij, à°³, Ý¥], [ðŁħ¢, ãĩº, â½Ĺ, â½Ĺ, ðŁıĩ, Ýĵ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 113], [166, 85], [136, 61], [83, 58], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[里, áĢı, ê³Ĥ, áĴĮ, ðŁıĩ, à¬ī, Ý¥], [ðIJŃĵ, á¥Ķ, â½Ĺ, â½Ĺ, Ôij, à°³, Ý¥], [ðŁħ¢, ãĩº, â½Ĺ, â½Ĺ, ðŁıĩ, Ýĵ, Ý¥], [áłĦ, ãī«, âĢ´, âĴ¡, ìľ¾, ë±IJ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_8><DEPTH_101><DEPTH_75><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_8><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_75><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[166, 111], [162, 78], [124, 57], [74, 58], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðIJŃĵ, á¥Ķ, â½Ĺ, â½Ĺ, Ôij, à°³, Ý¥], [ðŁħ¢, ãĩº, â½Ĺ, â½Ĺ, ðŁıĩ, Ýĵ, Ý¥], [áłĦ, ãī«, âĢ´, âĴ¡, ìľ¾, ë±IJ, Ý¥], [íĵ¶, ðĿĻ¿, á¤Ĭ, ðĿļı, áĮ½, áīIJ, Ý¥]]."
]
}
| null |
||
{
"from": [
"human",
"gpt"
],
"value": [
"The task is pick up the biscuit box and place it in the basket. What is the action that the robot should take. To figure out the action that the robot should take to pick up the biscuit box and place it in the basket, let's think through it step by step. First, what is the depth map for the first image? Second, how many subtasks are needed to complete this task, what is the semantic description of each subtask, and what are the goal positions for each subtask? Third, what is the trajectory of the end effector in the first image to reach the next subtask goal? Based on the depth map of the first image, the semantic description and goal position of each subtask, the trajectory of the end effector in the first image, along with other images from different camera views as additional information, what is the action that the robot should take?",
"The depth map of the first image is <DEPTH_START><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_69><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_56><DEPTH_101><DEPTH_32><DEPTH_56><DEPTH_75><DEPTH_26><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_26><DEPTH_26><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_56><DEPTH_32><DEPTH_32><DEPTH_32><DEPTH_8><DEPTH_101><DEPTH_101><DEPTH_69><DEPTH_32><DEPTH_32><DEPTH_101><DEPTH_69><DEPTH_56><DEPTH_56><DEPTH_8><DEPTH_26><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_8><DEPTH_56><DEPTH_32><DEPTH_101><DEPTH_101><DEPTH_32><DEPTH_75><DEPTH_75><DEPTH_32><DEPTH_56><DEPTH_56><DEPTH_32><DEPTH_75><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_56><DEPTH_56><DEPTH_56><DEPTH_101><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_75><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_101><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_75><DEPTH_26><DEPTH_26><DEPTH_75><DEPTH_26><DEPTH_55><DEPTH_25><DEPTH_55><DEPTH_28><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_55><DEPTH_28><DEPTH_END>. The number of subtasks is 1. The subtask goals are: place the biscuit box in the basket at [64, 63]. The trajectory of the end effector in the first image is [[167, 104], [162, 78], [124, 57], [74, 58], [64, 63]]. Based on these information, along with other images from different camera views as additional information, the action that the robot should take is [[ðŁħ¢, ãĩº, â½Ĺ, â½Ĺ, ðŁıĩ, Ýĵ, Ý¥], [áłĦ, ãī«, âĢ´, âĴ¡, ìľ¾, ë±IJ, Ý¥], [íĵ¶, ðĿĻ¿, á¤Ĭ, ðĿļı, áĮ½, áīIJ, Ý¥], [ðĿĻ¸, ðĿij³, á¸Ĭ, ðĿĵ¾, ìĿ©, ìĭ², Ý¥]]."
]
}
| null |
End of preview. Expand
in Data Studio
Robot Manipulation Dataset with Trajectory Annotations (Deluxe Edition)
Dataset Description
This enhanced dataset contains robot manipulation demonstrations with:
- Image observations: RGB images from robot camera
- Wrist camera views: End-effector perspective images
- Rich conversations: Task descriptions with semantic subtask annotations
- Trajectory annotations: Visual grounding through trajectory points
- Reverse trajectories: Return-to-initial-position augmented data
Dataset Structure
Fields
image: Primary camera RGB imagewrist: Wrist/end-effector camera imageconversations: Structured task dialogue- Task description with semantic subtask decomposition
- Depth map information
- Trajectory predictions
- Action token sequences
annotation: Trajectory coordinates (null for standard frames, populated for annotated frames)
Data Composition
This dataset combines:
- Forward task data: Complete task demonstrations with semantic descriptions
- Reverse trajectory data: Return-to-initial-position augmentation (shifted indices)
Total samples: ~42K+ (21K+ forward + 21K+ reverse)
Usage
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("DannyJun/real_spr_basket_v1")
train_data = dataset['train']
# Access sample
sample = train_data[0]
print("Task:", sample['conversations']['value'][0])
print("Annotation:", sample['annotation'])
Example Conversation Format
Human: The task is pick up the book and place it in the back compartment of the caddy. What is the action that the robot should take? To figure out the action that the robot should take, let's think through it step by step...
Assistant: The depth map of the first image is .... The number of subtasks is 2. The subtask goals are: pick up the book at [116, 49] and place the book in the back compartment of the caddy at [128, 71]. The trajectory of the end effector in the first image is [[116, 49], [120, 55], [128, 71]]...
Tasks Included
- Object placement and manipulation
- Container operations (microwave, drawer, cabinet)
- Multi-object coordination
- Sequential manipulation tasks
- Reverse trajectory tasks (return to initial position)
Citation
@dataset{robot_manipulation_deluxe,
title={Robot Manipulation Dataset with Trajectory Annotations (Deluxe Edition)},
year={2024},
publisher={Hugging Face},
url={https://huggingface.co/datasets/DannyJun/real_spr_basket_v1}
}
License
MIT License
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